https://github.com/xwjdsh/2048-ai

An simple AI for the 2048 game.
https://github.com/xwjdsh/2048-ai

2048 2048-game

Last synced: 3 months ago
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An simple AI for the 2048 game.

• Host: GitHub
• URL: https://github.com/xwjdsh/2048-ai
• Owner: xwjdsh
• License: mit
• Created: 2017-10-22T13:09:11.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2019-12-10T07:56:42.000Z (almost 5 years ago)
• Last Synced: 2024-06-20T03:45:33.677Z (5 months ago)
• Topics: 2048, 2048-game
• Language: Go
• Homepage:
• Size: 479 KB
• Stars: 318
• Watchers: 13
• Forks: 28
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 2048-AI

[![Build Status](https://travis-ci.org/xwjdsh/2048-ai.svg?branch=master)](https://travis-ci.org/xwjdsh/2048-ai)

[![Go Report Card](https://goreportcard.com/badge/github.com/xwjdsh/2048-ai)](https://goreportcard.com/report/github.com/xwjdsh/2048-ai)

[![](https://images.microbadger.com/badges/image/wendellsun/2048-ai.svg)](https://microbadger.com/images/wendellsun/2048-ai "Get your own image badge on microbadger.com")

[![DUB](https://img.shields.io/dub/l/vibe-d.svg)](https://github.com/xwjdsh/2048-ai/blob/master/LICENSE)

AI for the 2048 game, implements by expectimax search, powered by Go.

The web front-ends of 2048 game was forked from [gabrielecirulli/2048](https://github.com/gabrielecirulli/2048), respect and gratitude!

## Screenshot

![](https://raw.githubusercontent.com/xwjdsh/2048-ai/master/screenshot/2048-ai.jpg)

## How to run?

#### Via Go

```bash

go get github.com/xwjdsh/2048-ai

cd $GOPATH/src/github.com/xwjdsh/2048-ai

go build

./2048-ai

```

#### Via Docker

```shell

docker run -p 8080:8080 wendellsun/2048-ai

```

or build images by yourself:

```shell

# clone and enter project

docker build -t 2048-ai .

docker run -p 8080:8080 2048-ai

```

Then, you can access http://localhost:8080/ from the browser.

## Related

* [Expectimax search ](https://www.google.co.jp/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&cad=rja&uact=8&ved=0ahUKEwiVrsfmiojXAhWExbwKHa6GAuYQFgg3MAI&url=https%3A%2F%2Fweb.uvic.ca%2F~maryam%2FAISpring94%2FSlides%2F06_ExpectimaxSearch.pdf&usg=AOvVaw0pjG10MxUtkBvM-mvRNlew)

* [Model weight matrix](https://codemyroad.wordpress.com/2014/05/14/2048-ai-the-intelligent-bot/)

* Communication by websocket, implements by [gorilla/websocket](https://github.com/gorilla/websocket)

## Licence

[MIT License](https://github.com/xwjdsh/2048-ai/blob/master/LICENSE)